Emotion Detection and Regulation from Personal Assistant Robot in Smart Environment

Castillo, José Carlos; Castro‐González, Álvaro; Alonso-Martín, Fernándo; Fernández-Caballero, Antonio; Salichs, Miguel Á.

doi:10.1007/978-3-319-62530-0_10

Cited by 22 publications

(12 citation statements)

References 38 publications

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“…Miri and colleagues (2020) developed a haptic device to facilitate deep breathing during stressful situations. Castillo, Castro-González, Alonso-Martin, Fernández-Caballero, and S΄alichs (2018) proposed personal-assistant robots that regulate their owners’ emotional states, and Amores and Maes (2017) explored interfaces that release scent to influence mood and improve task performance.…”

Section: Computing Research Into Digital Ermentioning

confidence: 99%

Digital Emotion Regulation

Wadley

Smith

Koval

et al. 2020

Curr Dir Psychol Sci

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People routinely regulate their emotions in order to function more effectively at work, to behave more appropriately in social situations, or simply to feel better. Recently, researchers have begun to examine how people shape their affective states using digital technologies, such as smartphones. In this article, we discuss the emergence of digital emotion regulation, both as a widespread behavioral phenomenon and a new cross-disciplinary field of research. This field bridges two largely distinct areas of enquiry: (a) psychological research into how and why people regulate their emotions, which has yet to systematically explore the role of digital technology, and (b) computing research into how digital technologies impact users’ emotions, which has yet to integrate psychological theories of emotion regulation. We argue that bringing these two areas into better contact will benefit both and will facilitate a deeper understanding of the nature and significance of digital emotion regulation.

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Section: Computing Research Into Digital Ermentioning

confidence: 99%

Digital Emotion Regulation

Wadley

Smith

Koval

et al. 2020

Curr Dir Psychol Sci

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“…It should be recalled that the signals generated by the path planner are the (reference) inputs of the UAV’s controller which in the end calculates what (control) inputs should be applied to the aircraft to direct its flight correctly during the monitoring of the person. In this process, the information captured by the camera on board the UAV will be sent to a processing station for analysis using artificial intelligence techniques, such as emotion recognition [ 34 , 35 , 36 ], to determine the person’s physical condition and possible assistance [ 37 ].…”

Section: Trajectory Planningmentioning

confidence: 99%

Feeling of Safety and Comfort towards a Socially Assistive Unmanned Aerial Vehicle That Monitors People in a Virtual Home

Belmonte

García

Morales

et al. 2021

Sensors

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Unmanned aerial vehicles (UAVs) represent a new model of social robots for home care of dependent persons. In this regard, this article introduces a study on people’s feeling of safety and comfort while watching the monitoring trajectory of a quadrotor dedicated to determining their condition. Three main parameters are evaluated: the relative monitoring altitude, the monitoring velocity and the shape of the monitoring path around the person (ellipsoidal or circular). For this purpose, a new trajectory generator based on a state machine, which is successfully implemented and simulated in MATLAB/Simulink®, is described. The study is carried out with 37 participants using a virtual reality (VR) platform based on two modules, UAV simulator and VR Visualiser, both communicating through the MQTT protocol. The participants’ preferences have been a high relative monitoring altitude, a high monitoring velocity and a circular path. These choices are a starting point for the design of trustworthy socially assistive UAVs flying in real homes.

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“…The literature offers several approaches for face detection and recognition [19, 20]. Applications range from people recognition [21], surveillance [22] to emotion detection and regulation [23, 24]. Although there are several techniques to retrieve facial features, this problem is still challenging since most of the approaches are highly dependent on the face orientation.…”

Section: Related Workmentioning

confidence: 99%

Social Robotics in Therapy of Apraxia of Speech

Castillo

Álvarez-Fernández

Alonso-Martín

et al. 2018

Journal of Healthcare Engineering

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Apraxia of speech is a motor speech disorder in which messages from the brain to the mouth are disrupted, resulting in an inability for moving lips or tongue to the right place to pronounce sounds correctly. Current therapies for this condition involve a therapist that in one-on-one sessions conducts the exercises. Our aim is to work in the line of robotic therapies in which a robot is able to perform partially or autonomously a therapy session, endowing a social robot with the ability of assisting therapists in apraxia of speech rehabilitation exercises. Therefore, we integrate computer vision and machine learning techniques to detect the mouth pose of the user and, on top of that, our social robot performs autonomously the different steps of the therapy using multimodal interaction.

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Emotion Detection and Regulation from Personal Assistant Robot in Smart Environment

Cited by 22 publications

References 38 publications

Digital Emotion Regulation

Digital Emotion Regulation

Feeling of Safety and Comfort towards a Socially Assistive Unmanned Aerial Vehicle That Monitors People in a Virtual Home

Social Robotics in Therapy of Apraxia of Speech

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